Location: Pest Management Research
Project Number: 3032-21220-002-009-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Mar 1, 2019
End Date: Apr 1, 2020
Objective:
To test the hypothesis that inundation frequency is a primary control on Russian Olive distributions in western alluvial floodplains, Cooperators will conduct a correlative geospatial analysis with the prediction that Russian Olive cover will have a positive spatial association with small return intervals, i.e., portions of the floodplain inundated frequently.
Approach:
Geospatial Analyses
Data Sources.–Cooperators will utilize the hydraulic inundation models generated by the US Army Corps of Engineers [2016] that were based on peak streamflow estimates from Chase [2013]. These inundation models were generated using the United States Army Corps of Engineers state of the art Hydrologic Engineering Centers River Analysis System (HEC-RAS) software. Cooperators will utilize the Russian Olive cover geospatial dataset generated by Combs and Potter [2011]. Both geospatial datasets are freely available at the Yellowstone River Corridor Geographic Information Clearinghouse [2018].
Delineating the Floodplain.–Cooperators will define the Yellowstone River floodplain as the area of land within Fort Keogh predicted to be inundated during a 500-year flood event, as estimated by the US Army Corps of Engineers [2016].
Relating Return Interval to Russian Olive Cover.–Cooperators will generate an inundation zone map of the floodplain. The value of each pixel in this raster will be the most frequent return interval at which each pixel is estimated to inundate, as modeled by the US Army Corps of Engineers [2016]. Cooperators will convert the Russian Olive shapefile to a raster layer with two potential pixel values corresponding to whether the pixel was occupied or unoccupied by Russian Olive. Cooperators will then spatially quantify Russian Olive occupancy in the inundation zone map
Statistical Analysis.
Cooperators will conduct a Pearsons Chi-squared test to evaluate how likely it is that the spatial distribution of Russian Olive is independent of return interval in our study area.
